Various adaptive filter structures have been developed for use in time updated adaptive systems to solve acoustical echo cancellation, channel equalization and other problems; examples of such structures include for example, transversal, multistage lattice, systolic array, and recursive implementations. Among these, transversal finite-impulse-response (FIR) filters are often used, due to stability considerations, and to their versatility and ease of implementation. Many algorithms have also been developed to adapt these filters, including the least-mean-square (LMS), recursive least-squares, sequential regression, and least-squares lattice algorithms. The LMS algorithm is the most commonly used algorithm. It requires neither matrix inversion nor the calculation of correlation matrices, and therefore is often selected to perform the adaptation of the filter coefficients.
A deficiency of the LMS algorithm is that it requires the selection of a “seed” factor value (μ), also referred to as the step size or gain. The “seed” factor value (μ) permits the adaptation of the filter coefficients using the LMS method and also allows the filter coefficients to converge. The seed factor value (μ), which may be constant or variable, plays an important role in the performance of the adaptive system. For example, improper selection of the “seed” factor value (μ) may cause the adaptive filter to diverge thereby becoming unstable. For more details regarding the convergence properties, the reader is invited to refer to B. Widrow and Steams, S. D., Adaptive Signal Processing, Prentice-Hall, Englewood Cliffs, N.J., 1985. The content of this document is hereby incorporated by reference. A proper selection of the seed factor value (μ) requires knowledge of the characteristics of the signals that will be processed by the time updated adaptive filter. Consequently, a same “seed” factor value (μ) may be suitable in an adaptive filter in a first system and unsuitable in an adaptive filter in a second system due to the characteristics of the signals being processed.
Consequently, there is a need in the industry for providing a novel method and apparatus for adapting time updated filter that alleviates, at least in part, the deficiencies associated with existing method and apparatuses.